Simplicial Embeddings in Self-Supervised Learning and Downstream Classification

1 April 2022

Papers citing "Simplicial Embeddings in Self-Supervised Learning and Downstream Classification"

8 / 8 papers shown

Title
A Complexity-Based Theory of Compositionality Eric Elmoznino Thomas Jiralerspong Yoshua Bengio Guillaume Lajoie CoGe 61 4 0 18 Oct 2024
MAD-TD: Model-Augmented Data stabilizes High Update Ratio RL C. Voelcker Marcel Hussing Eric Eaton Amir-massoud Farahmand Igor Gilitschenski 39 1 0 11 Oct 2024
UniZero: Generalized and Efficient Planning with Scalable Latent World Models Yuan Pu Yazhe Niu Jiyuan Ren Zhenjie Yang Hongsheng Li Yu Liu OffRL 41 1 0 15 Jun 2024
Multi-CLS BERT: An Efficient Alternative to Traditional Ensembling Haw-Shiuan Chang Ruei-Yao Sun Kathryn Ricci Andrew McCallum 41 14 0 10 Oct 2022
Improving Self-Supervised Learning by Characterizing Idealized Representations Yann Dubois Tatsunori Hashimoto Stefano Ermon Percy Liang SSL 70 40 0 13 Sep 2022
Compressive Visual Representations Kuang-Huei Lee Anurag Arnab S. Guadarrama John F. Canny Ian S. Fischer SSL 62 48 0 27 Sep 2021
Emerging Properties in Self-Supervised Vision Transformers Mathilde Caron Hugo Touvron Ishan Misra Hervé Jégou Julien Mairal Piotr Bojanowski Armand Joulin 314 5,775 0 29 Apr 2021
Coordination Among Neural Modules Through a Shared Global Workspace Anirudh Goyal Aniket Didolkar Alex Lamb Kartikeya Badola Nan Rosemary Ke Nasim Rahaman Jonathan Binas Charles Blundell Michael C. Mozer Yoshua Bengio 154 98 0 01 Mar 2021